class_docstr: Callback for executing different checkpoint requirements.
docstr: Attr:
      config(mmf_typings.DictConfig): Config for the callback
      trainer(Type[BaseTrainer]): Trainer object
docstr_tok: ["Attr",":","config","(","mmf_typings.DictConfig",")",":","Config","for","the","callback","trainer","(","Type","[","BaseTrainer","]",")",":","Trainer","object"]
code: def __init__(self, config, trainer):
      """
      Attr:
          config(mmf_typings.DictConfig): Config for the callback
          trainer(Type[BaseTrainer]): Trainer object
      """
      super().__init__(config, trainer)
  
      self._checkpoint = Checkpoint(trainer)
      self.checkpoint_interval = (
          self.config.training.checkpoint_interval
      )
  
file_path: mmf/mmf/trainers/callbacks/checkpoint.py
imports: import logging
  from mmf.trainers.callbacks.base import Callback
  from mmf.utils.checkpoint import Checkpoint, consolidate_optim_state_dict
label_desc: Use image node_id 1 to create a new CheckpointCallback object from inherited base classes: Callback with example: obj = CheckpointCallback(config, trainer)